Paper Citation Record · LEDGER

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency

As of 20 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 7 inbound Pith citation observations for arXiv:2505.02133.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.02133 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T01:04:43.459105Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:15:48.502829Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-01T20:26:12.298078Z

Reference resolution

42 of 42 outbound references displayed

verified exact0
verified fuzzy13
unresolved29
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 63bb2c79-f556-49ea-a6f7-8a66d6ddcd94 · outbound

This paper cites GPT-4o System Card,.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency GPT-4o System Card,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:04:44.124310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 891f2155-9151-4dc2-ab21-4d87868b876f · outbound

This paper cites The Claude 3 Model Family: Opus, Sonnet, Haiku Anthropic.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency The Claude 3 Model Family: Opus, Sonnet, Haiku Anthropic

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:04:44.108135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 566dc2b3-0fb3-4fa0-9b48-e731c902a45c · outbound

This paper cites The Llama 3 Herd of Models.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency The Llama 3 Herd of Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.276300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34f46a74-908c-4b6c-8ef4-e2089dbbd57c · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency Gemini: A Family of Highly Capable Multimodal Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.281067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6cc477e-051d-41b4-a8a8-a5972107493f · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size,.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency Gemma 2: Improving Open Language Models at a Practical Size,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:04:44.092914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3cf27a4f-3245-4c05-be8a-9e65418cc5e5 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency LLaMA: Open and Efficient Foundation Language Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.290623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 356a5fc6-1917-4645-aa4d-33c03899eb1f · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.295716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f83eb6b-2293-489b-8372-f75c999c899d · outbound

This paper cites Qwen2 Technical Report,.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency Qwen2 Technical Report,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:04:44.078464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ed9ec64f-bb83-450b-a6ce-dc0377c002c2 · outbound

This paper cites Mixtral of Experts,.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency Mixtral of Experts,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:04:44.063122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6a816ab2-4977-4a41-9046-4cf92011ae6b · outbound

This paper cites Mistral 7B.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency Mistral 7B

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.310706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bd75353-218e-477c-8631-14995790576a · outbound

This paper cites DeepSeek-V3 Technical Report.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency DeepSeek-V3 Technical Report

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.315027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0fc007e-beb8-4ab2-8814-b75a364472a5 · outbound

This paper cites Zephyr: Direct Distillation of LM Alignment.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency Zephyr: Direct Distillation of LM Alignment

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.319213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8314428-cd69-4830-ab02-a5e74bfdba4f · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency Evaluating Large Language Models Trained on Code

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.323804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8efe2e37-41fc-4496-80eb-b096aca127c8 · outbound

This paper cites From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Future.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Future

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.327578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13c4f10b-ffe2-4cc2-9b95-ee16f70fd48a · outbound

This paper cites Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.331734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed483d6e-8357-407d-b9d9-70472e7a24f4 · outbound

This paper cites AgentCoder: Multi-Agent-based Code Generation with Iterative Testing and Optimisation.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency AgentCoder: Multi-Agent-based Code Generation with Iterative Testing and Optimisation

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.336200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3152481-f5b3-4957-8eb9-9c49009869ff · outbound

This paper cites MapCoder: Multi-Agent Code Generation for Competitive Problem Solving.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency MapCoder: Multi-Agent Code Generation for Competitive Problem Solving

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.340868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 397b354b-bcfc-42e0-a65e-f567584cbd13 · outbound

This paper cites Scaling Large Language Model-based Multi-Agent Collaboration.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency Scaling Large Language Model-based Multi-Agent Collaboration

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.345621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f205114c-7806-4330-9011-b1b6b66be203 · outbound

This paper cites ChatDev: Communicative Agents for Software Development.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency ChatDev: Communicative Agents for Software Development

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.350479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76be9be7-25f4-47af-a821-01f241a3546b · outbound

This paper cites MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework,.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:04:44.048565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a21010ec-3fb1-4770-8208-e1fcef4692ce · outbound

This paper cites Self-collaboration Code Generation via ChatGPT.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency Self-collaboration Code Generation via ChatGPT

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.359761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c38a6e5-4dc2-4946-8027-ad502f73829b · outbound

This paper cites CY- CLE: Learning to Self-Refine the Code Genera- tion,.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency CY- CLE: Learning to Self-Refine the Code Genera- tion,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.364308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5d92926-ae7b-4961-aa24-17b5e79640b3 · outbound

This paper cites Debug like a Hu- man: A Large Language Model Debugger via Ver- ifying Runtime Execution Step-by-step,.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency Debug like a Hu- man: A Large Language Model Debugger via Ver- ifying Runtime Execution Step-by-step,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:04:44.032991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5bbc7345-4b66-4432-9907-3920a25ce4e7 · outbound

This paper cites Leveraging Print Debugging to Improve Code Gen- eration in Large Language Models,.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency Leveraging Print Debugging to Improve Code Gen- eration in Large Language Models,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:04:44.015816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e5ea0a8e-e10e-46fa-b1b4-1e235c1b6bec · outbound

This paper cites RGD: Multi-LLM Based Agent Debugger via Refinement and Generation Guidance.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency RGD: Multi-LLM Based Agent Debugger via Refinement and Generation Guidance

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.378374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d3b70fd-2043-4a3b-b87b-43f975e65c9c · outbound

This paper cites From Code to Correctness: Closing the Last Mile of Code Gen- eration with Hierarchical Debugging,.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency From Code to Correctness: Closing the Last Mile of Code Gen- eration with Hierarchical Debugging,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:04:43.999252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 48863728-1fc6-4104-b23d-878133734bb2 · outbound

This paper cites SOEN-101: Code Generation by Emulating Software Process Models Using Large Language Model Agents.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency SOEN-101: Code Generation by Emulating Software Process Models Using Large Language Model Agents

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.392179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04b168da-97fc-41e5-b35e-d44deba62306 · outbound

This paper cites ReflectionCoder: Learning from Reflection Sequence for Enhanced One-off Code Generation.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency ReflectionCoder: Learning from Reflection Sequence for Enhanced One-off Code Generation

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.397129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce530737-14de-4e1a-9d60-7924b50b05db · outbound

This paper cites Teaching Large Language Models to Self-Debug,.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency Teaching Large Language Models to Self-Debug,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:04:43.985492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a0042412-a25e-4f03-971f-99b8954eee62 · outbound

This paper cites Program Synthesis with Large Language Models.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency Program Synthesis with Large Language Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.406271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc747d94-56fa-43eb-bcd3-e24efdf0b5cc · outbound

This paper cites Is Your Code Generated by ChatGPT Really Cor- rect? Rigorous Evaluation of Large Language Mod- els for Code Generation.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency Is Your Code Generated by ChatGPT Really Cor- rect? Rigorous Evaluation of Large Language Mod- els for Code Generation

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:04:43.969505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b74e3a94-0f41-4441-a020-d4bfe7c69838 · outbound

This paper cites BLOOM: A 176B-Parameter Open-Access Multilingual Language Model.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.415696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c15df1f-98a2-470d-b476-8660ae97f09a · outbound

This paper cites PaLM: Scaling Language Modeling with Pathways,.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency PaLM: Scaling Language Modeling with Pathways,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:04:43.953782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 87f81ae2-f6df-43d1-bf1b-ee63a9359b47 · outbound

This paper cites Qwen Technical Report,.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency Qwen Technical Report,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:04:43.937052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a5cb156e-f217-4a1c-a89a-9c90034eb762 · outbound

This paper cites DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.428961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36b8f8ac-2c08-4ec1-8412-7eccf762652b · outbound

This paper cites Code Llama: Open Foundation Models for Code.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency Code Llama: Open Foundation Models for Code

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.433479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37e5dbd0-3c1b-4c40-8042-9fb50580b369 · outbound

This paper cites WizardCoder: Empowering Code Large Language Models with Evol-Instruct.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency WizardCoder: Empowering Code Large Language Models with Evol-Instruct

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.437476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87ff476a-64d7-49c2-9ad7-c0aecf2585c8 · outbound

This paper cites StarCoder: may the source be with you!.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency StarCoder: may the source be with you!

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.441349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39909963-21db-4165-8d7f-221b5d1efbf5 · outbound

This paper cites Magicoder: Empowering Code Generation with OSS-Instruct.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency Magicoder: Empowering Code Generation with OSS-Instruct

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.445511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3399c2de-76b1-4782-a35a-ff29a92b24bb · outbound

This paper cites OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.449698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15b5655c-2c1c-4b8a-9e5e-d27cce6b770b · outbound

This paper cites StarCoder 2 and The Stack v2: The Next Generation.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency StarCoder 2 and The Stack v2: The Next Generation

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.454572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dee68f70-8c12-4d26-a275-425b2f933eac · outbound

This paper cites Reflexion: Language Agents with Verbal Reinforcement Learning.

Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency Reflexion: Language Agents with Verbal Reinforcement Learning

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-16T01:04:43.459105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 0793178c-9d13-43b2-9189-2a21611f57ec · inbound

Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI cites this paper.

Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency

Reference 176

Resolution: unresolved; no resolver link, observed 2026-08-07T14:15:48.502829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f8e2ab5-3c98-4d47-9e65-b73712e18143 · inbound

Position Paper: Programming Language Techniques for Bridging LLM Code Generation Semantic Gaps cites this paper.

Position Paper: Programming Language Techniques for Bridging LLM Code Generation Semantic Gaps Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T18:07:08.007222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 349621a9-5105-4119-ad89-854ca063cbbb · inbound

WildCode Revisited: A Comprehensive Empirical Study on the Security of LLM-Generated Code cites this paper.

WildCode Revisited: A Comprehensive Empirical Study on the Security of LLM-Generated Code Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T18:41:17.920359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ac82032-2948-4021-94d7-9ffae6761838 · inbound

Cascaded Code Editing: Large-Small Model Collaboration for Effective and Efficient Code Editing cites this paper.

Cascaded Code Editing: Large-Small Model Collaboration for Effective and Efficient Code Editing Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:56:05.616333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6d8f5d4b-db41-4aa0-9144-2998e43f7c0a · inbound

The Infinite Mutation Engine? Measuring Polymorphism in LLM-Generated Offensive Code cites this paper.

The Infinite Mutation Engine? Measuring Polymorphism in LLM-Generated Offensive Code Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-12T10:56:30.177624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 914550fb-d923-462a-b161-56bb1db492a3 · inbound

The Infinite Mutation Engine? Measuring Polymorphism in LLM-Generated Offensive Code cites this paper.

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:15:39.553334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation de17b9d3-59f7-4d1a-aee2-20ecf94db210 · inbound

How Generation Architecture Shapes Code Complexity in Multi-Agent LLM Systems: A Paired Study on HumanEval cites this paper.

How Generation Architecture Shapes Code Complexity in Multi-Agent LLM Systems: A Paired Study on HumanEval Enhancing LLM Code Generation: A Systematic Evaluation of Multi-Agent Collaboration and Runtime Debugging for Improved Accuracy, Reliability, and Latency

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-07-01T20:26:12.299701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.